考虑电源出力和负荷需求不确定性的影响，建立了新型电力系统“源-储”规划容量两阶段鲁棒优化模型。利用偶理论和卡罗需-库恩-塔克（Karush-Kuhn-Tucker conditions，KKT）条件，把具有min-max-min结构的鲁棒优化问题分解成主问题和子问题两阶段进行求解。主问题为最小化的优化问题结构，采用松弛形式，考虑了新型电力系统的碳排放要求以及弃风弃光的制约条件，确定各类电源的装机容量的最优值，得到原问题的最优解的上界。子问题为包含非线性变量的最大-最小化的优化问题结构，采用对偶理论和KKT条件进行建模，并利用Big-M法处理非线性约束条件，采用盒式不确定集描述风光出力的不确定场景，以第一阶段的优化结果为前提，确定各种最恶劣场景。算例中3个情景的仿真结果验证了所提模型和方法的可行性和适应性。

A two-stage robust optimization model for the planning capacity of the new power system "source-storage" of new power system is established, taking into account the uncertainty of power output and load demand. Using even theory and Karush Kuhn Tucker conditions (KKT), the robust optimization problem with min-max-min structure is decomposed into two stages: the main problem and sub problems for solution. The main problem is the minimization optimization problem structure, which adopts a relaxed form and considers the carbon emission requirements of new power system and the constraints of wind and solar power curtailment. The optimal values of the installed capacity of various power sources are determined, and the upper bound of the optimal solution of the original problem is obtained. The sub-problem is a maximum-minimum optimization problem structure containing nonlinear variables. It is modeled using dual theory and KKT conditions, and the Big-M method is used to handle nonlinear constraints. A box type uncertain set is used to describe the uncertain scenarios of wind and solar power output. Based on the optimization results of the first stage, various worst-case scenarios are determined. The simulation results of three scenarios in the example validate the feasibility and adaptability of the proposed model and method.